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Abstract:
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Opportunistic spectrum reuse is a promising solution to the two main causes of spectrum scarcity : most of the radio frequency (RF ) bands are allocated by static licensing , and many of them are underutilized . Frequency spectrum can be more efficiently utilized by allowing communication systems to find out unoccupied spectrum and to use it harmlessly to the licensed users . Reliable sensing of these spectral opportunities is perhaps the most essential element of this technology . Despite significant work on spectrum sensing , further performance improvement is needed to approach its full potential .
In this dissertation , wireless spectrum sensing networks (WSSNs ) are investigated for reliable detection of the primary (licensed ) users , that enables efficient spectrum utilization and minimal power consumption in communications . Reliable spectrum sensing is studied in depth in two parts : a single sensor algorithm and then cooperative sensing are proposed based on a spectral covariance sensing (SCS ) . The first novel contribution uses different statistical correlations of the received signal and noise in the frequency domain . This detector is analyzed theoretically and verified through realistic simulations using actual digital television signals captured in the US . The proposed SCS detector achieves significant improvement over the existing solutions in terms of sensitivity and also robustness to noise uncertainty . Second , SCS is extended to a distributed WSSN architecture to allow cooperation between 2 or more sensors . Theoretical limits of cooperative white space sensing under correlated shadowing are investigated . We analyze the probability of a false alarm when each node in the WSSN detects the white space using the SCS detection and the base station combines individual results to make the final decision . The detection performance compared with that of the cooperative energy detector is improved and fewer sensor nodes are needed to achieve the same sensitivity .
Third , we propose a low power source coding and modulation scheme for power efficient communication between the sensor nodes in WSSN . Complete analysis shows that the proposed scheme not only minimizes total power consumption in the network but also improves bit error rate (BER ) . |